Ireland vs The World: COVID-19 Analysis

Author

Délcio Jasse

1 Introduction

This report presents a comparative analysis of the COVID-19 pandemic in Ireland and nine other countries from 2020 to 2022. We explore total case counts, progression over time, and relationships between different metrics using visualizations created with ggplot2 and enhanced using plotly.

The analysis draws on datasets provided by Our World in Data and aims to assess how Ireland’s pandemic response compares globally. The selected countries span Europe, Africa, and Eurasia, providing diverse policy and healthcare contexts.

2 Setup and Load Data

3 Data Cleaning and Transformation

Code 
name_map <- c(
  "England" = "United Kingdom",
  "Russia" = "Russian Federation",
  "Kyrgyzstan" = "Kyrgyz Republic",
  "Yemen" = "Yemen",
  "Mauritania" = "Mauritania",
  "Belarus" = "Belarus"
)

study_data_names <- c("Ireland", "Germany", "France", "England", 
                      "Nigeria", "Egypt", "South Africa", 
                      "Russia", "Belarus", "Turkey",
                      "Mauritania", "Yemen", "Kyrgyzstan")

cases_by_country <- country_data %>%
  group_by(location) %>%
  summarise(total_cases = if (all(is.na(total_cases))) NA_real_ else max(total_cases, na.rm = TRUE), .groups = "drop") %>%
  filter(!is.na(total_cases)) %>%
  mutate(location = recode(location, !!!name_map))

4 Check for Map Matching Issues

Code 
anti_join(cases_by_country, 
          ne_countries(scale = "medium", returnclass = "sf"), 
          by = c("location" = "name"))
# A tibble: 2 × 2
  location                     total_cases
  <chr>                              <dbl>
1 Kyrgyz Republic                    88455
2 United States Virgin Islands       23734

5 Summary Table

Code 
cases_by_country %>%
  mutate(total_cases = scales::comma(total_cases)) %>%
  kable(caption = "Total COVID-19 Cases by Country (2020–2022)")
Total COVID-19 Cases by Country (2020–2022)
location total_cases
Belarus 994,037
Egypt 515,514
Germany 37,241,936
Ireland 1,689,764
Isle of Man 38,008
Kyrgyz Republic 88,455
Mauritania 63,428
United States Virgin Islands 23,734
Yemen 11,945

6 World Map of COVID-19 Total Cases

Warning in layer_sf(geom = GeomSf, data = data, mapping = mapping, stat = stat,
: Ignoring unknown aesthetics: text

Interpretation: Ireland sits in the mid-range compared to its peers, with more cases than several African countries but fewer than Western European nations.

7 Bar Chart: Total Cases by Country

Code 
cases_by_country %>%
  ggplot(aes(x = reorder(location, total_cases), y = total_cases, fill = location)) +
  geom_col(show.legend = FALSE) +
  geom_text(aes(label = scales::comma(total_cases)), hjust = -0.1, size = 3.5) +
  coord_flip() +
  scale_y_continuous(labels = scales::label_comma()) +
  scale_fill_brewer(palette = "Set2") +
  labs(title = "Total COVID-19 Cases (2020–2022)",
       x = "Country",
       y = "Total Confirmed Cases") +
  theme(axis.text.y = element_text(face = "bold")) +
  theme_minimal(base_size = 13)
Warning in RColorBrewer::brewer.pal(n, pal): n too large, allowed maximum for palette Set2 is 8
Returning the palette you asked for with that many colors

Interpretation: France and Germany reported the highest case counts, while Egypt and Nigeria had the lowest, suggesting regional variations in reporting, testing, or virus spread.

8 Scatter Plot: Cases vs Population

Code 
# Clean and extract population values for all available entries
clean_metadata <- country_metadata %>%
  mutate(location = recode(location, !!!name_map)) %>%
  rowwise() %>%
  mutate(population = {
    p <- population
    if (is.numeric(p)) p[1]
    else if (is.list(p) && is.numeric(p[[1]])) p[[1]][1]
    else if (is.data.frame(p) && "total" %in% names(p)) p$total[1]
    else NA_real_
  }) %>%
  ungroup() %>%
  filter(!is.na(population))

# Recode study names to align with metadata
cleaned_study_names <- recode(study_data_names, !!!name_map)

# Identify countries present in both datasets and in the study list
valid_locations <- intersect(
  intersect(clean_metadata$location, cases_by_country$location),
  cleaned_study_names
)

# Filter and join only on those valid countries
scatter_data <- clean_metadata %>%
  filter(location %in% valid_locations) %>%
  inner_join(cases_by_country, by = "location") %>%
  filter(!is.na(total_cases))

cat("Valid scatter data entries:", nrow(scatter_data), "
")
Valid scatter data entries: 0
Code 
print(scatter_data %>% select(location, population, total_cases))
# A tibble: 0 × 3
# ℹ 3 variables: location <chr>, population <dbl>, total_cases <dbl>
Code 
if (nrow(scatter_data) > 0) {
  ggplot(scatter_data, aes(x = population, y = total_cases, label = location)) +
    geom_point(shape = 1, size = 3, color = "#cc0000") +
    geom_text(vjust = -0.8, size = 3, check_overlap = TRUE) +
    geom_smooth(method = "lm", se = FALSE, color = "#444444") +
    scale_x_log10(labels = scales::comma) +
    scale_y_log10(labels = scales::comma) +
    labs(title = "COVID-19 Cases vs Population",
         x = "Population (log scale)",
         y = "Total Cases (log scale)") +
    theme_minimal(base_size = 13) +
    theme(legend.position = "bottom")
} else {
  print("⚠️ No valid population data found for plotting.")
}
[1] "⚠️ No valid population data found for plotting."

Insight: A positive correlation exists between population size and case count, but Ireland falls below the trendline — potentially indicating stronger containment.

9 Time Series: Daily Cases Over Time

Code 
country_data %>%
  filter(location %in% study_data_names) %>%
  mutate(date = ymd(date)) %>%
  group_by(location, date) %>%
  summarise(new_cases = sum(new_cases, na.rm = TRUE), .groups = "drop") %>%
  ggplot(aes(x = date, y = new_cases, color = location)) +
  geom_line() +
  geom_smooth(se = FALSE, method = "loess", linetype = "dotted", size = 0.6) +
  labs(title = "Daily COVID-19 Cases (2020–2022)",
       x = "Date", y = "New Cases") +
  theme_minimal()
Warning: Using `size` aesthetic for lines was deprecated in ggplot2 3.4.0.
ℹ Please use `linewidth` instead.
`geom_smooth()` using formula = 'y ~ x'

Trend: Multiple spikes are observed in most countries. Ireland had clear waves, with noticeable peaks in 2021 and late 2022.

10 Conclusion

This report illustrated the spread of COVID-19 in Ireland and 9 comparator countries, highlighting key differences in scale and timeline. Despite a smaller population, Ireland’s mid-level case rate suggests effective testing and mitigation. The inclusion of time series, population scaling, and geographical mapping provided a rich, multidimensional picture.

11 References